Search Results (1,352)

With the rapid increase in global lithium demand, the exploration of newly discovered lithium in the bauxite of the Wenshan area in southeastern Yunnan has become increasingly important. However, the current research on clay-type lithium in the Wenshan area has primarily focused on local exploration, and large-scale predictive metallogenic studies remain limited. To address this, this study utilized multi-source remote sensing data from ZY1-02D and ASTER, combined with ALOS 12.5 m DEM and Sentinel-2 imagery, to carry out remote sensing mineral identification, structural interpretation, and prospectivity mapping for clay-type lithium in the Wenshan area. This study indicates that clay-type lithium in the Wenshan area is controlled by NW, EW, and NE linear structures and are mainly distributed in the region from north of the Wenshan–Malipo fault to south of the Guangnan–Funing fault. High-value areas of iron-rich silicates and iron–magnesium minerals revealed by ASTER data indicate lithium enrichment, while montmorillonite and cookeite identification by ZY1-02D have strong indicative significance for lithium. Field verification samples show the highest Li₂O content reaching 11,150 μg/g, with six samples meeting the comprehensive utilization criteria for lithium in bauxite (Li₂O ≥ 500 μg/g) and also showing an enrichment of rare earth elements (REEs) and gallium (Ga). By integrating stratigraphic, structural, mineral identification, geochemical characteristics, and field verification data, ten mineral exploration target areas were delineated. This study validates the effectiveness of remote sensing technology in the exploration of clay-type lithium and provides an applicable workflow for similar environments worldwide. Full article

This study assesses the accuracy of flood extent predictions in five U.S. watersheds. We generated flood maps for four return periods using various digital elevation models (DEMs)—FABDEM, SRTM, ALOS, and USGS 3DEP—and two versions of the GEOGLOWS River Forecast System (RFS) hydrography. These comparisons are notable because they build on operational global hydrology models so subsequent work can develop global modeled flood products. Models were made using the Automated Rating Curve (ARC) and Curve2Flood tools. Accuracy was measured against USGS reference maps using the F-statistic. Our results show that flood map accuracy generally increased with higher return periods. The most consistent and reliable improvements in accuracy occurred when both the DEM and hydrography datasets were upgraded to higher-resolution sources. While DEM improvements generally had a greater impact, hydrography refinements were more important for lower return periods when flood extents were the smallest. Generally, DEM resolution improved accuracy metrics more as the return period increased and hydrography and bare earth DEMs mattered more as the return period decreased. There was a 38.9% increase in the mean F-statistic between the two principal pairings of interest (FABDEM-RFS2 and SRTM 30 m DEM-RFS1). FABDEM’s bare-earth representation combined with RFS2 sometimes outperformed higher-resolution non-bare-earth DEMs, suggesting that there remains a need for site-specific investigation. Using ARC and Curve2Flood with FABDEM and RFS2 is a suitable baseline combination for general flood extent application. Full article

Aloe vera gel is a valuable raw material used in the cosmetic industry for its skin care properties. The present study analyzed the effects of the fermentation of aloe vera gel with a tea fungus kombucha, which is a symbiotic consortium of bacteria and yeast, carried out for 10 and 20 days (samples F10 and F20, respectively). The resulting ferments and unfermented gel were subjected to chromatographic analysis to determine the content of biologically active compounds. The permeability and accumulation of these compounds in pig skin were evaluated. In addition, the methods of DPPH, ABTS and the determination of intracellular free radical levels in keratinocytes (HaCaT) and fibroblasts (HDF) cell lines were used to determine antioxidant potential. The results showed a higher content of phenolic acids and flavonoids and better antioxidant properties of the ferments, especially after 20 days of fermentation. Cytotoxicity tests against HaCaT and HDF cells confirmed the absence of toxic effects; moreover, samples at the concentrations tested (mainly 10 and 25 mg/mL) showed cytoprotective effects. The analysis of enzymatic activity (collagenase, elastase and hyaluronidase) by the ELISA technique showed higher levels of inhibition for F10 and F20. The kombucha ferments also exhibited better moisturizing properties and lower levels of transepidermal water loss (TEWL), confirming their cosmetic potential. Full article

Rapid and comprehensive assessment of building damage caused by earthquakes is essential for effective emergency response and rescue efforts in the immediate aftermath. Advanced technologies, including real-time simulations, remote sensing, and multi-sensor systems, can effectively enhance situational awareness and structural damage evaluations. However, most existing methods rely on isolated time snapshots, and few studies have systematically explored the continuous, time-scaled integration and update of building damage estimates from multiple data sources. This study proposes a stepwise framework that continuously updates time-scaled, single-damage estimation outputs using the best available multi-sensor data for estimating earthquake-induced building damage. We demonstrated the framework using the 2024 Noto Peninsula Earthquake as a case study and incorporated official damage reports from the Ishikawa Prefectural Government, real-time earthquake building damage estimation (REBDE) data, and satellite-based damage estimation data (ALOS-2-building damage estimation (BDE)). By integrating the REBDE and ALOS-2-BDE datasets, we created a composite damage estimation product (integrated-BDE). These datasets were statistically validated against official damage records. Our framework showed significant improvements in accuracy, as demonstrated by the mean absolute percentage error, when the datasets were integrated and updated over time: 177.2% for REBDE, 58.1% for ALOS-2-BDE, and 25.0% for integrated-BDE. Finally, for stepwise damage estimation, we proposed a methodological framework that incorporates social media content to further confirm the accuracy of damage assessments. Potential supplementary datasets, including data from Internet of Things-enabled home appliances, real-time traffic data, very-high-resolution optical imagery, and structural health monitoring systems, can also be integrated to improve accuracy. The proposed framework is expected to improve the timeliness and accuracy of building damage assessments, foster shared understanding of disaster impacts across stakeholders, and support more effective emergency response planning, resource allocation, and decision-making in the early stages of disaster management in the future, particularly when comprehensive official damage reports are unavailable. Full article

The development of bio-based adhesives as sustainable alternatives to synthetic formulations presents a significant opportunity for advancing environmental sustainability in packaging applications. This research aimed to develop and evaluate a bio-based adhesive derived from bacterial nanocellulose (BNC), aloe vera and its mixtures as a potential replacement for commercial synthetic adhesives. Aloe vera, selected for its polysaccharide-rich composition, served as a natural polymeric matrix, while BNC contributed reinforcing properties. The adhesive formulations, with and without BNC, were compared to a commercial adhesive to assess their mechanical performance. T-peel and shear tests were conducted on smooth and rough paper substrates to evaluate adhesive strength. The bio-based adhesive incorporating BNC demonstrated superior shear and peel strength on rough substrates due to enhanced mechanical interlocking within the fibrous structure of paper, whereas performance on smooth surfaces was hindered by uneven BNC distribution, reducing adhesive-substrate interaction. Although the commercial adhesive achieved higher absolute maximum force values, the bio-based formulation exhibited comparable mechanical stability under specific conditions. These findings underscore the influence of substrate properties and application methods on adhesive performance, highlighting the potential of bio-based adhesives in packaging applications and the need for further formulation optimization to fully realize their advantages over traditional synthetic adhesives. Full article

Water body detection in synthetic aperture radar (SAR) imagery plays a critical role in applications such as disaster response, water resource management, and environmental monitoring. However, it remains challenging due to complex background interference in SAR images. To address this issue, a bi-encoder and hybrid feature fuse network (BiEHFFNet) is proposed for achieving accurate water body detection. First, a bi-encoder structure based on ResNet and Swin Transformer is used to jointly extract local spatial details and global contextual information, enhancing feature representation in complex scenarios. Additionally, the convolutional block attention module (CBAM) is employed to suppress irrelevant information of the output features of each ResNet stage. Second, a cross-attention-based hybrid feature fusion (CABHFF) module is designed to interactively integrate local and global features through cross-attention, followed by channel attention to achieve effective hybrid feature fusion, thus improving the model’s ability to capture water structures. Third, a multi-scale content-aware upsampling (MSCAU) module is designed by integrating atrous spatial pyramid pooling (ASPP) with the Content-Aware ReAssembly of FEatures (CARAFE), aiming to enhance multi-scale contextual learning while alleviating feature distortion caused by upsampling. Finally, a composite loss function combining Dice loss and Active Contour loss is used to provide stronger boundary supervision. Experiments conducted on the ALOS PALSAR dataset demonstrate that the proposed BiEHFFNet outperforms existing methods across multiple evaluation metrics, achieving more accurate water body detection. Full article

Ravine forests are key to conserving biodiversity and maintaining ecosystem processes in fragmented landscapes. Here, we evaluated the phenology of plant species in the Los Nogales Nature Sanctuary (Lo Barnechea, Chile) using Sentinel-2 images (2019–2024) and the Alos Palsar DEM (12.5 m). We calculated the Normalized Difference Vegetation Index (NDVI), the Topographic Position Index (TPI), and Diurnal Anisotropic Heat (DAH) to assess vegetation dynamics across different topographic and thermal gradients. Generalized Additive Models (GAM) revealed that tree species exhibited more stable, regular seasonal NDVI trajectories, while shrubs showed moderate fluctuations, and herbaceous species displayed high interannual variability, likely reflecting sensitivity to climatic events. Spatial analysis indicated that trees predominated on steep slopes and higher elevations, herbs were concentrated in low-lying, moisture-retaining areas, and shrubs were more common in areas with higher thermal load. These findings highlight the significant role of terrain and temperature in shaping plant phenology and distribution, underscoring the utility of remote sensing and topographic indices for monitoring ecological processes in complex mountainous environments. Full article

The envelopes of Red Supergiants (RSGs) have a unique chemical environment not seen in other types of stars. They foster an oxygen-rich synthesis but are tempered by sporadic and chaotic mass loss, which distorts the envelope and creates complex outflow sub-structures consisting of knots, clumps, and arcs. Near the stellar photosphere, molecules and grains form under approximate LTE conditions, as predicted by chemical models. However, the complicated outflows appear to have distinct chemistries generated by shocks and dust destruction. Various RSG envelopes have been probed for their molecular content, mostly by radio and millimeter observations; however, VY Canis Majoris (VY CMa) and NML Cygni (NML Cyg) display the highest chemical complexity, and also the most complicated envelope structure. Thus far, over 29 different molecules have been identified in the envelopes of RSGs. Some molecules are common for circumstellar gas, including CO, SiO, HCN and H₂O, which have abundances of ∼10⁻⁶–10⁻⁴, relative to H₂. More exotic oxides have additionally been discovered, such as AlO, AlOH, PO, TiO₂, and VO, with abundances of ∼10⁻⁹–10⁻⁷. RSG shells support intricate maser emission in OH, H₂O and SiO, as well. Studies of isotope ratios in molecules suggest dredge-up at least into the H-burning shell, but further exploration is needed. Full article

Aim: To prepare two different kinds of wound care creams containing plant extracts and examine their effectiveness in comparison with a placebo cream and a commercial wound care cream, Madecassol^®. Methods: The two cream formulations were developed using the same placebo cream (PC) as base cream. One formulation contained balsam of oriental sweet gum, or Levant storax, named as Levant Storax Cream (LSC); the other contained oil of Calendula, extract of St. John’s Wort, aescin (an extract of horse chestnut), and freeze-dried powder from Aloe vera (L.) Burm. f. leaf juice, designated as Complex Cream (CC). In the characterization of the creams, organoleptic properties, pH, viscosity, size distribution, and zeta potential of oil globules were measured. Furthermore, the stability of the creams was assessed under different environmental conditions. In vitro studies were performed by using an excisional wound model in rats to assess the potential of the creams for stimulating wound healing. The efficacy of LSC and CC was compared with a commercial reference cream, Madecassol^® (M), and the placebo control. The study was also designed with a negative control group of rats that were not treated but handled the same way as the other treatment groups. The wound contraction rate, total skin thickness recovery, and results of histopathological parameter examinations were used to compare the effectiveness of the treatments. Results: The stability of formulated creams confirmed that they were stable for the duration of the study. In vivo studies showed that rats treated with LSC achieved the highest wound healing rates when compared with the other groups. A better response was recorded for the CC-treated population when compared to both control and placebo groups, but there was no significant difference seen in healing score between CC and M groups. Full article

Aloin, a kind of active phenolic component, is sourced from Aloe vera. Recently, the determination of aloin has received enormous attention, owing to its positive performance (including anti-tumor, antibacterial, detoxification, liver protection, anti-stomach damage, and skin protection activities) and painful side effects (increased carcinogenicity caused by excessive use of aloin) impacting human health. This investigation was inspired by the good fluorescence properties of carbon dots (CDs); CD-based sensors have aroused a great deal of interest due to their excellent sensitivity and selectivity. Thus, it is of great significance to develop novel CD-based sensors for aloin determination. Herein, N,F-CDs were designed and synthesized through a convenient hydrothermal strategy; the synthesized N,F-CDs possessed good fluorescence performance and a small particle size (near 4.3 nm), which demonstrated the successful preparation of N,F-CDs. The resulting N,F-CDs possessed a large Stokes shift and could emit a highly stable green fluorescence. The fluorescence of the N,F-CDs could be effectively quenched by aloin through the inner filter effect. Furthermore, the synthesis procedure was easy to operate. Finally, the N,F-CD-coated test strips were fabricated and combined with a miniaturized fluorimeter for the fluorescence detection of aloin via the inner filter effect for the first time. The N,F-CD-coated test strips were fabricated and used for the fluorescence sensing of aloin, and the results were compared with a typical ultraviolet (UV) method. The N,F-CD-coated test strips exhibited high recovery (96.9~106.1%) and sensitivity (31.8 nM, n = 3), good selectivity, low sample consumption (1 μL), high speed (5 min), good stability, and anti-interference properties. The results indicate that N,F-CD-coated test strips are applicable for the quantitative determination of aloin in bovine serum, orange juice, and urine samples. Full article

The airborne Synthetic Aperture Radar (SAR) has the advantages of high-precision real-time observation of wave height variations and portability in the high frequency band, such as the Ku band. In view of the Four Fast Fourier Transform (4-FFT) algorithm, combined with a Gaussian operator, a Laplacian of Gaussian (LoG) Phase Unwrapping (PU) expression was derived. Then, an Adaptive LoG (ALoG) algorithm was proposed based on adaptive variance, further optimizing the algorithm through iteration. Building the models of Kelvin wake on the sea surface and height to phase, the interferometric phase of wave height can be simulated. These PU algorithms were qualitatively and quantitatively evaluated. The Principal Component Analysis (PCA) scores of the ALoG iteration (ALoGI) algorithm are the best under the tested noise levels of the simulation. Through a simulation experiment, it has been proven that the superiority of the ALoGI algorithm in high spatial resolution inversion for the sea-ship surface height of the Kelvin wake, with good stability and noise resistance. Full article

Integrating multi-source remote sensing can improve the accuracy of forest aboveground biomass (AGB) estimation. However, the accuracy and stability of the forest AGB estimation results are affected by multiple remote sensing feature variables as well as parameter tuning of machine learning algorithms. To this end, this study employed six types of remote sensing data—Landsat 8 OLI, Sentinel-2A, GEDI, ICESat-2, ALOS-2, and SAOCOM. A dual-variable selection strategy based on SHapley Additive exPlanations (SHAP) was developed, and a genetic algorithm (GA) was used to optimize the parameters of five machine learning models—elastic net (EN), least absolute shrinkage and selection operator (Lasso), support vector regression (SVR), Random Forest (RF), and Categorical Boosting (CatBoost)—to estimate the AGB of Pinus kesiya var. langbianensis forest in Wuyi Village, Zhenyuan County. The dual-variable selection strategy integrates SHAP with the Pearson correlation coefficient (PC), RF, EN, and Lasso to enhance feature screening robustness and interpretability. The results of the study showed that Lasso-SHAP dual-variate screening was more stable than SHAP univariate screening. In particular, the Lasso-SHAP strategy improved the average R² from 0.59 (using SHAP alone) to above 0.70, achieving an enhancement of 11%. Among GA-optimized parametric machine learning models, the linear GA-Lasso achieved the best performance, with an R² of 0.91 and an RMSE of 12.94 Mg/ha, followed by the GA-EN model (R² = 0.89, RMSE = 14.46 Mg/ha). For nonlinear models, GA-SVR performed the best (R² = 0.74, RMSE = 22.07 Mg/ha), surpassing the GA-CatBoost model (R² = 0.64, RMSE = 25.88 Mg/ha). In summary, the Lasso-SHAP dual-variable selection strategy effectively improves the estimation accuracy of AGB for Pinus kesiya var. langbianensis forests, while GA-optimized machine learning models demonstrate excellent performance, providing strong support for regional-scale forest resource monitoring and carbon stock assessment. Full article

Microbeads of raspberry extract were produced using encapsulation matrices alginate + pea protein isolate + psyllium mucilage, alginate + pea protein isolate + psyllium mucilage + okra, and alginate + pea protein isolate + psyllium mucilage + Aloe ferox gel + gallic acid using freeze-drying method. The microbeads were characterised and assessed for their effectiveness on the release, bioaccessibility, of anthocyanin components and antioxidant activities during in vitro digestion. Alginate + pea protein isolate + psyllium mucilage + Aloe ferox gel + gallic acid matrix showed the highest encapsulation efficiency of 91.60% while the lowest encapsulation efficiency was observed in alginate + pea protein isolate + psyllium mucilage + okra (69.94%). Scanning electron microscope images revealed spherical shapes and varying surface morphologies for different encapsulation matrices. Despite the differences observed in Fourier transform infrared spectra, microbeads showed similar thermal degradation patterns. X-ray diffractograms showed amorphous structures for different encapsulation matrices. Comparatively, alginate+ pea protein isolate + psyllium mucilage + Aloe ferox gel + gallic acid microbeads exhibited the highest bioaccessibility for total phenols (93.14%), cyanidin-3-O-sophoroside (54.61%), and cyanidin-3-O-glucoside (55.30%). The encapsulation matrices of different biopolymer combinations (alginate+ pea protein isolate+ psyllium mucilage, alginate + pea protein isolate + psyllium mucilage + okra, and alginate + pea protein isolate + psyllium mucilage + Aloe ferox gel + gallic acid) enhanced anthocyanin stability and protected it against in vitro degradation of bioactive compounds. Full article

The southwestern mountainous region of China (SMRC), characterized by complex geological environments, experiences frequent landslide disasters that pose significant threats to local residents. This study focuses on the Qijiang District of Chongqing, where we conduct a systematic evaluation of wavelength and observation geometry effects on InSAR-based landslide monitoring. Utilizing multi-sensor SAR imagery (Sentinel-1 C-band, ALOS-2 L-band, and LUTAN-1 L-band) acquired between 2018 and 2025, we integrate time-series InSAR analysis with geological records, high-resolution topographic data, and field investigation findings to assess representative landslide-susceptible zones in the Qijiang District. The results indicate the following: (1) L-band SAR data demonstrates superior monitoring precision compared to C-band SAR data in the SMRC; (2) the combined use of LUTAN-1 ascending/descending orbits significantly improved spatial accuracy and detection completeness in complex landscapes; (3) multi-source data fusion effectively mitigated limitations of single SAR systems, enhancing identification of small- to medium-scale landslides. This study provides critical technical support for multi-source landslide monitoring and early warning systems in Southwest China while demonstrating the applicability of China’s SAR satellites for geohazard applications. Full article

This study examines the environmental challenges posed by azo-dye pollutants and aluminum industrial waste. Aluminum oxide nanoparticles (P/Al₂O₃-NPs) were produced using a green method that utilized pharmaceutical packaging waste as an aluminum source and marine algae extract (Padina pavonica) as reducing and stabilizing agents and that was characterized by XRD, EDX, SEM, TEM, and zeta potential. Batch biosorption studies were performed to assess the effectiveness of P/Al₂O₃-NPs in removing CR dye from aqueous solutions. The results demonstrate that the particle sizes range from 58.63 to 86.70 nm and morphologies vary from spherical to elliptical. FTIR analysis revealed Al–O lattice vibrations at 988 and 570 cm⁻¹. The nanoparticles displayed a negative surface charge (−13 mV) and a pH_zpc of 4.8. Adsorption experiments optimized parameters for CR dye removal, achieving 97.81% efficiency under native pH (6.95), with a dye concentration of 30 mg/L, an adsorbent dosage of 0.1 g/L, and a contact time of 30 min. Thermodynamic studies confirmed that the process is exothermic and spontaneous. Kinetic data fit well with the pseudo-second-order model, while equilibrium data aligned with the Langmuir isotherm. The adsorption mechanism involved van der Waals forces, hydrogen bonding, and π–π interactions, as supported by the influence of pH, isotherm data, and FTIR spectra. Overall, the study demonstrates the potential of eco-friendly P/Al₂O₃-NPs to efficiently remove CR dye from aqueous solutions. Full article